The invention relates generally to the field of medical diagnostics, and more particularly to an evaluating system for obtaining diagnostic information from signals and data of medical sensor systems by means of measurement data and patient databases.
To an increasing extent in medical diagnosis use is made of systems which obtain diagnostic information from signals and data derived from the patient. This group of systems also includes the automatically evaluating electrocardiographs (EKG apparatus).
EKG evaluating systems, e.g. according to U.S. Pat. No. 5,022,404, detect one or more electrode potentials of electrodes attached to the patient, and filter and digitalized them. Then these signals are fed via a multiplexer to a microcomputer with CPU, work memory, etc. existing in the EKG evaluating system. The computer processes the measured signals, e.g. by removal of the baseline drift according to DE 41 06 856, U.S. Pat. No. 5,357,969 or the removal of muscle artefacts from the EKG according to U.S. Pat. No. 5,259,387. Moreover, it calculates the medical derivations necessary for medical analysis of the EKG according to Wilson, Goldberg, Einthoven and/or the orthogonal derivations according to Frank. At its simplest these medical derivations are either shown on paper strips and/or electronic displays, e.g. in U.S. Pat. No. 5,022,404 on LCDs, and evaluated by the doctor doing the evaluation. More intelligent, so-called evaluating electrocardiographs use the microcomputer existing in the apparatus for, apart from signal processing and display, also signal evaluation, signal measurement and, if occasion arises, for the output of diagnostic information such as e.g. in U.S. Pat. No. 5,029,082.
Signal measurement and evaluation are effected, as described in patents of which more details are given below, as a rule in such a way that from the calculated medical derivations are determined a number of individual signal parameters important for cardiological assessment of the EKG with respect to time and amplitude or criteria derived therefrom. A problem with this determination of individual signal parameters is the different approaches, such as e.g. in exact determination of the zero line of the EKG for determining the starting point of the P wave and the resulting determination of the duration of the P wave, which deliver quite substantially differing results depending on the quality of the method used. The patents are amongst others DE 43 10 412 (evaluation of the ST segment or other T wave), DE 39 27 709 (evaluation of the ST section), U.S. Pat. No. 5,159,932 (filtering of the EKG, QRS finding, averaging) or U.S. Pat. No. 5,020,540 (analysis of the frequency structure of the QRST complex, waveform template). Further relevant patents contain determination of individual parameters of the EKG, or serve to detect limited diagnostic information, e.g. in U.S. Pat. No. 4,930,075 (evaluation of the ST segment for the detection of ischemias), U.S. Pat. No. 5,025,794 (method of bidirectional filtering for the detection of retarded potentials), U.S. Pat. No. 5,355,891 (automatic signal averaging by beat triggering for the detection of retarded potentials), U.S. Pat. No. 5,341,811 (HP filtering of at least two channels, weigh adaptive filters for common-mode rejection, retarded potential detection) or DE43 04 269 (evaluation of the ST section for the assessment of acute ischemic damage).
The signal parameters determined are printed out on the paper strip or indicated directly together with the signal path of the EKG. For the output of diagnostic information, in a more or less complicated branched decision tree the individual signal parameters determined are linked together into meaningful diagnostic information. This is done for example by the many programs forming the basis of computer EKG apparatus. Such decision trees can have for example the following form: xe2x80x9cIf parameter 1 occurs in conjunction with parameter 3 and/or parameter 4 and in medical derivation a at the same time condition 1 is operative, from this can be inferred the diagnostic information xyzxe2x80x9d. In this way for every known diagnosis a decision tree can be built up on the basis of individual signal parameters determined from the EKG in its derivations. This method is extremely elaborate on account of the large number of influencing variables and parameters and requires extensive cardiological knowledge or experience. Changes or improvements in the methods for determining individual parameters, control of empirically determined threshold values or new medical knowledge require sometimes elaborate program alterations and function tests and are therefore associated with high costs or require new EKG apparatus with the revised programs. The patent U.S. Pat. No. 5,355,892 therefore describes an EKG system with portable storage media (floppy disk drive) for the storage of both EKG and patient information, e.g. for hospital information systems, as well as for reloading or updating algorithms for EKG evaluation.
A more recent group of EKG apparatus or methods try to obtain limited diagnostic information from the EKG signal by means of adaptive neuronal networks such as e.g. DE 43 07 545 (multi-channel measurement of electrical and/or magnetic field variables at least during part of the heart cycle, evaluations with an adaptive classifier (neuronal network for the classification and location of ischemias and/or infarctions) or U.S. Pat. No. 5,280,792 (arrhythmia classification by means of a combination of time analysis and sample comparison as well as neuronal networks). A problem with these methods is both the high learning effort in training the neuronal networks and the fact that neuronal networks are themselves at the stage of applied basic research. A full analysis of an EKG with the aim of deriving complex diagnostic information requires, on account of the complexity of an EKG, a very high number of neurons or, associated with this, a very high computing capacity.
A further group of EKG apparatus or methods serves for the analysis and diagnosis of rhythm disturbances, e.g. for cardiac pacemakers or direct control of defibrillators. These include e.g. patents DE 32 09 850 (classification of rhythm disturbances, evaluation by comparison of the complete curve of the EKG with EKG curves of the patient under examination detected or calculated previously in a learning phase, full storage of an example of the EKG curve for each class of rhythm disturbances of the patient under examination), U.S. Pat. No. 5,240,009 (detection of rhythm disturbances by comparison of averaged and stored waveform complexes with current complexes of the same patient), U.S. Pat. No. 5,217,012 (correlation of result-free portions of own EKG with areas of the EKG with rhythm disturbances, compression and storage of the result-free EKG areas, alarm criterion is exceeding the threshold value of cross-correlation function) or DE 43 20 519 (measurement and comparison of three heartbeat periods and then of at least fifty heartbeat curves, diagnosis of heart rhythm disturbances). A common feature of all these methods is that in each case they test only certain diagnostic groups or given individual features of the EKG.
The invention makes it possible to derive diagnostic information with high reliability from recorded signals and data of electrical and/or magnetic medical measurement systems, without reducing the measurement data initially to more or less complex individual characteristics which depend on the progress of knowledge, and then linking these individual characteristics by means of decision tress or neural networks which are difficult to modify, into diagnostic information.
It is the object of the invention to make the obtaining of diagnostic information from the measurement data of medical measurement systems, such as EKG systems, largely independent of the more or less complex evaluation of individual characteristics, which change constantly with the progress of knowledge, and decision trees based on those characteristics or the comprehensive process of training neural networks. According to the invention the object is achieved by the fact that a comparator compares measurement data of a patient from one or more sensor channels with all or some of the measurement data of comparable sensor channels of reference measurements stored in one or more measurement databases and selects the reference measurements which have the greatest similarity to the patient""s measurement with respect to the measurement data of comparable sensor channels and also a maximum possible number of sensor channels which match most in the measurement data and correspond to each other. A probability is also inferred from a comparison of the technical, medical, diagnostic and personal information belonging to the reference measurements of the measurement database and the patients"" diagnostic information.